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Database and information-retrieval methods for knowledge discovery

Authors:

Gerhard Weikum,

Gjergji Kasneci,

Maya Ramanath,

Fabian SuchanekAuthors Info & Claims

Communications of the ACM, Volume 52, Issue 4

Pages 56 - 64

https://doi.org/10.1145/1498765.1498784

Published: 01 April 2009 Publication History

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Abstract

Comprehensive knowledge bases would tap the Web's deepest information sources and relationships to address questions beyond today's keyword-based search engines.

References

[1]

Agichtein, E. Scaling information extraction to large document collections. IEEE Data Engineering Bulletin 28, 4 (Dec. 2005), 3--10.

Google Scholar

[2]

Amer-Yahia, S, and Lalmas, M. XML search: Languages, INEX, and scoring. ACM SIGMOD Record 35, 4 (Mar. 2006), 16--23.

Digital Library

Google Scholar

[3]

Anyanwu, K., Maduko, A., and Sheth, A. SPARQ2L: Towards support for subgraph extraction queries in RDF databases. In Proceedings of the 16th International Conference on World Wide Web (Banff, Canada, May 8--12). ACM Press, New York, 2007, 797--806.

Digital Library

Google Scholar

[4]

Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., and Ives, Z. DBpedia: A nucleus for a Web of open data., In Proceedings of the Sixth International Semantic Web Conference (Pusan, Korea, Nov. 11--15). Springer, Berlin/Heidelberg, 2007, 722--735.

Digital Library

Google Scholar

[5]

Banko, M., Cafarella, M., Soderland, S., Broadhead, M., and Etzioni, O. Open information extraction from the Web. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (Hyderabad, India, Jan. 6--12, 2007), 2670--2676; www.ijcai.org.

Digital Library

Google Scholar

[6]

Cafarella, M., Re, C., Suciu, D., and Etzioni, O. Structured querying of Web text data: A technical challenge. In Proceedings of the Third Biennial Conference on Innovative Data Systems Research (Asilomar, CA, Jan. 7--10, 2007), 225--234; www.crdrdb.org.

Google Scholar

[7]

Chakrabarti, S. Dynamic personalized PageRank in entity-relation graphs. In Proceedings of the 16th International Conference on World Wide Web (Banff, Canada, May 8--12). ACM Press, New York, 2007, 571--580.

Digital Library

Google Scholar

[8]

Cheng, T., Yan, X., and Chang, K. Entity Rank Searching entities directly and holistically. In Proceedings of the 33rd International Conference on Very Large Data Bases (Vienna, Austria, Sept. 23--27). ACM Press, New York, 2007, 387--398.

Digital Library

Google Scholar

[9]

Cohen, W. Integration of heterogeneous databases without common domains using queries based on textual similarity. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Seattle, June 2--4). ACM Press, New York. 1998, 201--212.

Digital Library

Google Scholar

[10]

Cunningham, H. An introduction to information extraction. In Encyclopedia of Language and Linguistics, Second Edition, K. Brown et al., Eds., Elsevier, Amsterdam, 2005.

Google Scholar

[11]

DeRose, P., Shen, W., Chen, F., Doan, A.-H., and Ramakrishnan, R. Building structured Web community portals: A top-down, compositional, and incremental approach. In Proceedings of the 33rd International Conference on Very Large Data Bases (Vienna, Austria, Sept. 23--27). ACM Press, New York. 2007, 399--410.

Digital Library

Google Scholar

[12]

Etzioni, O., Cafarella, M., Downey, D., Popescu, A.-M., Shaked, T., Soderland, S., Weld, D., and Yates, A. Unsupervised named-entity extraction from the Web: An experimental study. Artificial Intelligence 165, 1 (June 2005), 91--134.

Digital Library

Google Scholar

[13]

Fuhr, N. and Rölleke, T. A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Transactions on Information Systems 15, 1 (Jan. 1997), 32--66.

Digital Library

Google Scholar

[14]

Fuhr, N. Probabilistic datalog: A logic for powerful retrieval methods. In Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Seattle. July 9--13). ACM Press, New York 1995, 282--290.

Digital Library

Google Scholar

[15]

Getoor, L. and Taskar, B., Eds. Introduction to Statistical Relational Learning, MIT Press, Cambridge, MA, 2007.

Digital Library

Google Scholar

[16]

Ilyas, I., Beskales, G., and Soliman, M. A survey of top-k query-processing techniques in relational database systems. ACM Computing Surveys 40, 1 (Oct. 2008), 1--58.

Digital Library

Google Scholar

[17]

Ipeirotis, P., Agichtein, E., Jain, P., and Gravano, L. Towards a query optimizer for text-centric tasks. ACM Transactions on Database Systems 32, 4 (Nov. 2007).

Digital Library

Google Scholar

[18]

Kasneci, G., Suchanek, F., Ifrim, G., Ramanath, M., and Weikum, G. NAGA: Searching and ranking knowledge. In Proceedings of the 24th International Conference on Data Engineering (Cancun, Mexico, Apr. 7--12). IEEE Computer Society, Washington, D.C., 2008, 953--62.

Digital Library

Google Scholar

[19]

Navarro, G. and Baeza-Yates, R. Proximal nodes: A model to query document databases by content and structure. ACM Transactions on Information Systems 15, 4(1997), 400--435.

Digital Library

Google Scholar

[20]

Nie, Z., Ma, Y., Shi, S., Wen, J.-R., and Ma, W.-Y. Web object retrieval. In Proceedings of the 16th International Conference on World Wide Web (Banff, Canada, May 8--12). ACM Press, New York, 2007, 81--90.

Digital Library

Google Scholar

[21]

Sarawagi, S. Information extraction. Foundations and Trends in Databases 1, 3 (2008), 261--377.

Digital Library

Google Scholar

[22]

Shen, W., Doan, A.H., Naughton, J., and Ramakrishnan, R. Declarative information extraction using datalog with embedded extraction predicates. In Proceedings of the 33rd International Conference on Very Large Databases (Vienna, Austria, Sept. 23--27). ACM Press, New York, 2007, 1033--1044.

Digital Library

Google Scholar

[23]

Suchanek, F., Kasneci, G., and Weikum, G. YAGO: A large ontology from Wikipedia and WordNet. Journal of Web Semantics 6, 3 (2008), 203--217.

Digital Library

Google Scholar

[24]

Suchanek, F., Kasneci, G., and Weikum, G. YAGO: A core of semantic knowledge. In Proceedings of the 16th International Conference on World Wide Web (Banff, Canada, May 8--12). ACM Press, New York. 2007, 697--706.

Digital Library

Google Scholar

[25]

Theobald, M., Bast, H., Majumdar, D., Schenkel, R., and Weikum, G. TopX: Efficient and versatile top-k query processing for semistructured data. VLDB Journal 17, 1 (Jan. 2008), 81--115.

Digital Library

Google Scholar

[26]

Wu, F. and Weld, D. Automatically refining the Wikipedia infobox ontology. In Proceedings of the 17th International Conference on World Wide Web (Beijing, Apr. 21--25). ACM Press, New York, 2008. 635--644.

Digital Library

Google Scholar

[27]

Wu, F. and Weld, D. Autonomously semantifying Wikipedia. In Proceedings of the 16th ACM Conference on Information and Knowledge Management (Lisbon, Nov. 6--10). ACM Press, New York, 2007, 41--50.

Digital Library

Google Scholar

[28]

Zhu, J., Nie, Z., Wen, J.-R., Zhang, Bo, and Ma, W.-Y. Simultaneous record detection and attribute labeling in Web data extraction. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Philadelphia. PA, Aug. 20--23). ACM Press, New York, 2006, 494--503.

Digital Library

Google Scholar

Cited By

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Krishnan SKrishnan L(2023)AI Driving Game Changing Trends in Project Delivery and Enterprise PerformanceProceedings of World Conference on Artificial Intelligence: Advances and Applications10.1007/978-981-99-5881-8_4(35-49)Online publication date: 2-Nov-2023
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Wu QWang PWang XHe XZhu WWu QWang PWang XHe XZhu W(2022)Question Answering (QA) BasicsVisual Question Answering10.1007/978-981-19-0964-1_3(27-31)Online publication date: 13-May-2022
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Nastase VSzpakowicz SNakov PSéagdha D(2021)Semantic Relations Between Nominals, Second EditionSynthesis Lectures on Human Language Technologies10.2200/S01078ED2V01Y202002HLT04914:1(1-234)Online publication date: 7-Apr-2021
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Database and information-retrieval methods for knowledge discovery

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Published In

Communications of the ACM Volume 52, Issue 4

A Direct Path to Dependable Software

April 2009

134 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/1498765

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2009

Published in CACM Volume 52, Issue 4

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Krishnan SKrishnan L(2023)AI Driving Game Changing Trends in Project Delivery and Enterprise PerformanceProceedings of World Conference on Artificial Intelligence: Advances and Applications10.1007/978-981-99-5881-8_4(35-49)Online publication date: 2-Nov-2023
https://doi.org/10.1007/978-981-99-5881-8_4
Wu QWang PWang XHe XZhu WWu QWang PWang XHe XZhu W(2022)Question Answering (QA) BasicsVisual Question Answering10.1007/978-981-19-0964-1_3(27-31)Online publication date: 13-May-2022
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Nastase VSzpakowicz SNakov PSéagdha D(2021)Semantic Relations Between Nominals, Second EditionSynthesis Lectures on Human Language Technologies10.2200/S01078ED2V01Y202002HLT04914:1(1-234)Online publication date: 7-Apr-2021
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Lederer MRiedl J(2020)Data Science Techniques in Knowledge-Intensive Business ProcessesInternational Journal of Data Analytics10.4018/IJDA.20200101041:1(52-67)Online publication date: Jan-2020
https://doi.org/10.4018/IJDA.2020010104
Zhu HZhang CCao ZTang R(2016)On efficient conditioning of probabilistic relational databasesKnowledge-Based Systems10.1016/j.knosys.2015.10.01792:C(112-126)Online publication date: 15-Jan-2016
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Szymański JRzeniewicz J(2016)Identification of category associations using a multilabel classifierExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.05.03961:C(327-342)Online publication date: 1-Nov-2016
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Gomes LSantanchè A(2015)The Web Within: Leveraging Web Standards and Graph Analysis to Enable Application-Level Integration of Institutional DataTransactions on Large-Scale Data- and Knowledge-Centered Systems XIX10.1007/978-3-662-46562-2_2(26-54)Online publication date: 24-Feb-2015
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ZHANG XASANO YYOSHIKAWA M(2014)Mining Knowledge on Relationships between Objects from the WebIEICE Transactions on Information and Systems10.1587/transinf.E97.D.77E97.D:1(77-88)Online publication date: 2014
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Barceló PLibkin LReutter J(2014)Querying Regular Graph PatternsJournal of the ACM10.1145/255990561:1(1-54)Online publication date: 1-Jan-2014
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Langer PSchulze PGeorge SKohnen MMetzke TAbedjan ZKasneci G(2014)Assigning global relevance scores to DBpedia facts2014 IEEE 30th International Conference on Data Engineering Workshops10.1109/ICDEW.2014.6818334(248-253)Online publication date: Mar-2014
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Abstract

References

Cited By

Index Terms

Recommendations

Knowledge Discovery from Academic Search Engine

Evaluating subtopic retrieval methods: Clustering versus diversification of search results

Knowledge Discovery and Data Visualization: Theories and Perspectives

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